Systems and methods for orientation independent sensing

ABSTRACT

A system and method for obtaining an OIS coordinate frame comprising an electronic control unit configured to determine a local 3D electric field loop, create a zero mean version of E(t) over a depolarization interval, compute an Ė value at each of a plurality of time intervals, compute an initial estimate of ŵ from a cross product of E and the Ė value for each of the plurality of time intervals, average the initial estimate of ŵ from each of the plurality of time for a best estimate of ŵ, determine a plurality of â(θ) values and using the corresponding {circumflex over (n)}(θ) values, compute a composite match score, and choose at least one best value for â and a best value for {circumflex over (n)}.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.16/230,969, filed 21 Dec. 2018 (the '969 application), which is acontinuation of U.S. application Ser. No. 15/152,496, filed 11 May 2016(the '496 application), now U.S. Pat. No. 10,194,994, which claims thebenefit of U.S. provisional application No. 62/160,376, filed 12 May2015 (the '376 application). The '969 application, '496 application and'376 application are all hereby incorporated by reference as thoughfully set forth herein.

BACKGROUND a. Field

This disclosure relates to systems, apparatuses and methods forutilizing electrode spatial arrangements within a mapping system. Inparticular, the instant disclosure relates to systems, apparatuses andmethods for characterizing cardiac conduction conditions in a catheterorientation independent manner using electrode spatial arrangements in3D mapping systems.

b. Background

Electrophysiology (EP) catheters are used in a variety of diagnostic,therapeutic, and/or mapping and ablative procedures to diagnose and/orcorrect conditions such as atrial or ventricular arrhythmias, includingfor example, ectopic atrial tachycardia, atrial fibrillation, and atrialflutter. Arrhythmias can create a variety of conditions includingirregular heart rates, loss of synchronous atrioventricular contractionsand stasis of blood flow in a chamber of a heart which can lead to avariety of symptomatic and asymptomatic ailments and even death.

Typically, a catheter is deployed and manipulated through a patient'svasculature to the intended site, for example, a site within a patient'sheart. The catheter carries one or more electrodes that can be used forcardiac mapping or diagnosis, ablation and/or other therapy deliverymodes, or both, for example. Once at the intended site, treatment caninclude, for example, radio frequency (RF) ablation, cryoablation, laserablation, chemical ablation, high-intensity focused ultrasound-basedablation, microwave ablation, and/or other ablation treatments. Thecatheter imparts ablative energy to cardiac tissue to create one or morelesions in the cardiac tissue. This lesion disrupts undesirable cardiacactivation pathways and thereby limits, corrals, or prevents errantconduction signals that can form the basis for arrhythmias.

To position a catheter at a desired site within the body, some type ofnavigation may be used, such as using mechanical steering featuresincorporated into the catheter (or a sheath). In some examples, medicalpersonnel may manually manipulate and/or operate the catheter using themechanical steering features.

A navigating system may be used for visualization and to facilitate theadvancement of catheters through a patient's vasculature to specificlocations within the body. Such navigating systems may include, forexample, electric and/or magnetic field based positioning and navigatingsystems that are able to determine the position and orientation of thecatheter (and similar devices) within the body.

Conduction disorders in the body can result from abnormal conduction inregions as small as 1-4 mm. In addition, ablation in these regions mustbe restricted to the pathological tissue to preserve electrical andmechanical function, particularly with ventricular arrhythmias. Today,many catheters employ electrode pairs spaced greater than 4 mm apartwhich can make it difficult to reliably allow discrimination orlocalization of defects. Even when the electrodes are more closelyspaced, around 1 mm to around 2 mm, the orientation of the pair ofelectrodes is a prominent factor in the amplitude and morphology of theresulting signals.

The foregoing discussion is intended only to illustrate the presentfield and should not be taken as a disavowal of claim scope.

BRIEF SUMMARY

In one embodiment, a system for obtaining an OIS coordinate framecomprises an electronic control unit configured to determine a local 3Delectric field loop, create a zero mean version of E(t) over adepolarization interval, compute an Ė value at each of a plurality oftime intervals, compute an initial estimate of ŵ from a cross product ofE and the Ė value for each of the plurality of time intervals, averagethe initial estimate of ŵ from each of the plurality of time for a bestestimate of ŵ, determine a plurality of â(θ) values and choosing acorresponding {circumflex over (n)}(θ) value for each of the pluralityof â(θ) values, compute a composite match score, and choose at least onebest value for a and a best value for {circumflex over (n)}.

In another embodiment, a method for obtaining an OIS coordinate framecomprises determining a local 3D electric field loop, creating a zeromean version of E(t) over a depolarization interval, computing an Ėvalue at each of a plurality of time intervals, computing an initialestimate of ŵ from a cross product of E and the Ė value for each of theplurality of time intervals, averaging the initial estimate of ŵ fromeach of the plurality of time for a best estimate of ŵ, determining aplurality of â(θ) values and choosing a corresponding {circumflex over(n)}(θ) value for each of the plurality of â(θ) values, computing acomposite match score, and choosing at least one best value for â and abest value for {circumflex over (n)}.

In yet another embodiment, a system for obtaining an OIS coordinateframe comprises an electronic control unit configured to determine alocal 3D electric field loop, compute a composite match score for howwell {dot over (φ)} matches an inner product of E and â(θ) and −φmatches an inner product of E and {circumflex over (n)}, choose a bestvalue for â and a best value for {circumflex over (n)}, and determine avalue for ŵ by a right hand rule and a cross product ŵ={circumflex over(n)}×â.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a diagrammatic view of a system for generating surface modelsand/or mapping electrophysiological information thereon.

FIG. 1B is simplified diagrammatic and schematic view of a modelconstruction system of the system illustrated in FIG. 1A.

FIG. 2A is an isometric view of one embodiment of a paddle catheter.

FIG. 2B is an isometric view of another embodiment of a paddle catheter.

FIG. 2C is an isometric view of another embodiment of a paddle catheter.

FIG. 3 is an isometric view of a basket catheter.

FIG. 4 is an illustration showing the activation, wavecrest, surfacenormal, and conduction velocity directions for a traveling wave.

FIG. 5 is a schematic illustrating electrode location and cliquegeometry.

FIG. 6 is a flow chart showing a step-by-step approach to acquire,determine, and output orientation independent information.

FIG. 7 is a diagrammatic view of helical basket catheter design withnon-uniform electrode spacing along splines but uniform spacing over theellipsoidal basket surface.

FIG. 8 is a diagram of a paddle catheter and the electrodes andrectangular cliques present on the paddle catheter.

FIG. 9 is a graph of the trajectory of vector E_(t) over a single beat.

FIG. 10A is a graph showing the EGM signals and equivalent bipole oromnipole E_(a) vs. time.

FIG. 10B is a line drawing of a shape of an exemplary E_(a).

FIG. 11 is a graph showing the time interval that holds the mostinformation about depolarizing tissue under a particular clique ofelectrodes.

FIG. 12 is a plot showing the weighting function vs. time.

FIG. 13 is a graph of an E-field loop showing regions of large and smalld/dt(E(t)).

FIGS. 14A and 14B are graphs showing the tangent E-field loop before andafter weighting the loop points based on the norm of the E-field.

FIGS. 15A and 15B are graphs showing the conduction velocity estimatedfrom two cliques over successive beats.

FIG. 16 is a flow diagram outlining the steps for obtaining an OIScoordinate frame.

FIG. 17 is one embodiment of an E-field loop and OIS coordinates.

FIG. 18A is a side view of a catheter coming in contact with a tissue.

FIG. 18B is a side view of a catheter distending the tissue in FIG. 18A.

DETAILED DESCRIPTION

Cardiac EP mapping today primarily uses bipolar electrograms (EGMs)obtained from electrode pairs. Bipoles are preferred as they havereduced low frequency noise, reduced far-field effects and often producesharp and well-recognized features when filtered appropriately. UnipolarEGMs on the other hand contain far-field information and less stablebaselines that make them less attractive for mapping purposes. A featureof the unipolar signal that makes it useful for mapping is the fact thatits morphology and amplitude are independent of catheter orientation.Amplitudes and morphology of bipolar EGM's are dependent on theorientation of the electrode pair from which they are calculated andhence depend on the orientation of the catheter. The dependence onorientation results in inconsistently measured amplitudes andmorphology-based measurements like activation times. It therefore alsoimpacts derived quantities like scar boundaries, activation direction,and conduction velocity.

Electrophysiologic information may also be elicited by pacing a tissueor organ and observing the resulting spread of depolarization fromimmediately adjacent to the site where capture occurs. Theseobservations are difficult with current technology because of pacingartifacts but directional information provided by E_(n), E_(a), or v, asdescribed herein, can serve as clues to anatomic or functionalconduction blocks. Even without pacing, conduction around obstacles suchas valve orifices or blocks is known to become curved and slowed andthis can be directly mapped and visualized with the informationdisclosed herein much more conveniently and reliably than previouslypossible.

FIG. 1A illustrates one embodiment of a system 160 for mappingelectrophysiological information corresponding to an anatomic structureonto a multi-dimensional (e.g., three-dimensional) geometry surfacemodel of the anatomic structure (each of the terms “electrophysiology”and “electrophysiological” will hereinafter be referred to as “EP”). Thesystem 160 comprises, among other components, a medical device 162 and amodel construction system 164. In one embodiment, the medical device 162comprises a catheter, and the model construction system 164 comprises,in part, a processing apparatus 166. The processing apparatus 166 maytake the form of an electronic control unit, for example, that isconfigured to obtain a geometry surface model of the cardiac structure,and to construct an EP map corresponding to the cardiac structure usingdata collected by, for example, the catheter 162. The catheter 162 isconfigured to be inserted into a patient's body 168, and moreparticularly, into the patient's heart 170. The catheter 162 may includea cable connector or interface 172, a handle 174, a shaft 176 having aproximal end 178 and a distal end 180 and one or more sensors 182 (e.g.,182 ₁, 182 ₂, 182 ₃) mounted in or on the shaft 176 of the catheter 162.In one embodiment, the sensors 182 are disposed at or near the distalend 180 of the shaft 176. The connector 172 provides mechanical, fluid,and electrical connection(s) for cables, such as, for example, cables184, 186 extending to the model construction system 164 and/or othercomponents of the system 160 (e.g., a visualization, navigation, and/ormapping system (if separate and distinct from the model constructionsystem 164), an ablation generator, irrigation source, etc.).

The sensors 182 mounted in or on the shaft 176 of the catheter 162 areelectrically connected to the model construction system 164, and theprocessing apparatus 166 thereof, in particular. The sensors 182 may beprovided for a variety of diagnostic and therapeutic purposes including,for example and without limitation, EP studies, pacing, cardiac mapping,and ablation. In an embodiment, one or more of the sensors 182 areprovided to perform a location or position sensing function.Accordingly, in such an embodiment, as the catheter 162 is moved along asurface of the cardiac structure and/or about the interior thereof, thesensor(s) 182 can be used to collect location data points thatcorrespond to the surface of, or locations within, the cardiacstructure. These location data points can then be used by, for example,the model construction system 164 in the construction of a geometrysurface model of the cardiac structure.

In one embodiment, the model construction system 164, and the processingapparatus 166 thereof, in particular, is configured to obtain a geometrysurface model of the cardiac surface (or at least a portion thereof),and to map EP information corresponding to that cardiac structure ontothe geometry surface model. The processing apparatus 166 is configuredto use, at least in part, data (location data and/or EPdata/information) collected by the catheter 162 in the construction ofone or both of a geometry surface model and an EP map.

In an embodiment wherein the model construction system 164 is configuredto construct the geometry surface model, the model construction system164 is configured to acquire location data points collected by thesensor(s) 182 corresponding to the cardiac structure. The modelconstruction system 164 is configured to then use those location datapoints in the construction of the geometry surface model of the cardiacstructure. The model construction system 164 is configured to constructa geometry surface model based on some or all of the collected locationdata points. In addition to constructing a geometry surface model of astructure, the model construction system 164 is configured to functionwith the sensor(s) 182 to collect location data points that are used inthe construction of the geometry surface model. In such an embodiment,the model construction system 164 may comprise an electric field-basedsystem, such as, for example, the EnSite NavX™ system commerciallyavailable from St. Jude Medical, Inc., and generally shown withreference to U.S. Pat. No. 7,263,397 entitled “Method and Apparatus forCatheter Navigation and Location and Mapping in the Heart”, the entiredisclosure of which is incorporated herein by reference. In otherexemplary embodiments, however, the model construction system 164 maycomprise other types of systems, such as, for example and withoutlimitation: a magnetic-field based system such as the Carto™ Systemavailable from Biosense Webster, and as generally shown with referenceto one or more of U.S. Pat. No. 6,498,944 entitled “IntrabodyMeasurement,” U.S. Pat. No. 6,788,967 entitled “Medical Diagnosis,Treatment and Imaging Systems,” and U.S. Pat. No. 6,690,963 entitled“System and Method for Determining the Location and Orientation of anInvasive Medical Instrument,” the entire disclosures of which areincorporated herein by reference, or the gMPS system from MediGuideLtd., and as generally shown with reference to one or more of U.S. Pat.No. 6,233,476 entitled “Medical Positioning System,” U.S. Pat. No.7,197,354 entitled “System for Determining the Position and Orientationof a Catheter,” and U.S. Pat. No. 7,386,339 entitled “Medical Imagingand Navigation System,” the entire disclosures of which are incorporatedherein by reference; a combination electric field-based and magneticfield-based system such as the Carto 3™ System also available fromBiosense Webster.

In one embodiment, the sensor(s) 182 of the catheter 162 comprisepositioning sensors. The sensor(s) 182 produce signals indicative ofcatheter location (position and/or orientation) information. In anembodiment wherein the model construction system 164 is an electricfield-based system, the sensor(s) 182 may comprise one or moreelectrodes. In such an embodiment, each of the electrodes may compriseone of a number of types of electrodes, such as, for example, tipelectrodes, ring electrodes, button electrodes, coil electrodes, brushelectrodes, flexible polymer electrodes, and spot electrodes.Alternatively, in an embodiment wherein the model construction system164 is a magnetic field-based system, the sensor(s) 182 may comprise oneor more magnetic sensors configured to detect one or morecharacteristics of a low-strength magnetic field. For instance, in oneexemplary embodiment, the sensor(s) 182 may comprise magnetic coilsdisposed on or in the shaft 176 of the catheter 162.

For purposes of clarity and illustration, the model construction system164 will hereinafter be described as comprising an electric field-basedsystem, such as, for example, the EnSite NavX™ system identified above.It will be appreciated that while the description below is primarilylimited to an embodiment wherein the sensor(s) 182 comprise one or moreelectrodes, in other exemplary embodiments, the sensor(s) 182 maycomprise one or more magnetic field sensors (e.g., coils). Accordingly,model construction systems that include positioning sensor(s) other thanthe sensors or electrodes described below remain within the spirit andscope of the present disclosure.

With reference to FIG. 1B, in addition to the processing apparatus 166,the model construction system 164 may include, among other possiblecomponents, a plurality of patch electrodes 188, a multiplex switch 190,a signal generator 192, and a display device 194. In another exemplaryembodiment, some or all of these components are separate and distinctfrom the model construction system 164 but that are electricallyconnected to, and configured for communication with, the modelconstruction system 164.

The processing apparatus 166 may comprise a programmable microprocessoror microcontroller, or may comprise an application specific integratedcircuit (ASIC). The processing apparatus 166 may include a centralprocessing unit (CPU) and an input/output (I/O) interface through whichthe processing apparatus 166 may receive a plurality of input signalsincluding, for example, signals generated by patch electrodes 188 andthe sensor(s) 182, and generate a plurality of output signals including,for example, those used to control and/or provide data to, for example,the display device 194 and the switch 190. The processing apparatus 166may be configured to perform various functions, such as those describedin greater detail above and below, with appropriate programminginstructions or code (i.e., software). Accordingly, the processingapparatus 166 is programmed with one or more computer programs encodedon a computer storage medium for performing the functionality describedherein.

With the exception of the patch electrode 188B called a “belly patch,”the patch electrodes 188 are provided to generate electrical signalsused, for example, in determining the position and orientation of thecatheter 162. In one embodiment, the patch electrodes 188 are placedorthogonally on the surface of the body 168 and are used to createaxes-specific electric fields within the body 168.

In one embodiment, the sensor(s) 182 of the catheter 162 areelectrically coupled to the processing apparatus 166 and are configuredto serve a position sensing function. More particularly, the sensor(s)182 are placed within electric fields created in the body 168 (e.g.,within the heart) by exciting the patch electrodes 188. For purposes ofclarity and illustration only, the description below will be limited toan embodiment wherein a single sensor 182 is placed within the electricfields. It will be appreciated, however, that in other exemplaryembodiments that remain within the spirit and scope of the presentdisclosure, a plurality of sensors 182 can be placed within the electricfields and then positions and orientations of each sensor can bedetermined using the techniques described below.

When disposed within the electric fields, the sensor 182 experiencesvoltages that are dependent on the location between the patch electrodes188 and the position of the sensor 182 relative to tissue. Voltagemeasurement comparisons made between the sensor 182 and the patchelectrodes 188 can be used to determine the location of the sensor 182relative to the tissue. Accordingly, as the catheter 162 is swept aboutor along a particular area or surface of interest, the processingapparatus 166 receives signals (location information) from the sensor182 reflecting changes in voltage levels on the sensor 182 and from thenon-energized patch electrodes 188. Using various known algorithms, theprocessing apparatus 166 may then determine the location (position andorientation) of the sensor 182 and record it as a location data pointcorresponding to a location of the sensor 182 on the surface of, orwithin, the cardiac structure in a memory or storage device associatedwith, or accessible, by the processing apparatus 166, such as the memory197. In one embodiment, prior to recording the location as a locationdata point, the raw location data represented by the signals received bythe processing apparatus 166 may be corrected by the processingapparatus 166 to account for respiration, cardiac activity, and otherartifacts using known or hereafter developed techniques. The systemdescribed in FIGS. 1A and 1B is further described in U.S. applicationSer. No. 14/533,630, filed 5 Nov. 2014, which is hereby incorporated byreference as though fully set forth herein.

One aspect described herein addresses a unique way to combine thebenefit of orientation independence of the unipolar signals with theother benefits of bipolar signals that were highlighted previously. Thedisclosure utilizes closely spaced electrodes on high-density diagnosticcatheters to derive local “pseudo bipolar”, “equivalent bipole”, or“omnipolar” signals that are catheter orientation independent and arefree of low-frequency noise and far-field effects. The closely spacedelectrodes can be located on a single high-density diagnostic or othercatheter or in some embodiments can be located on multiple catheterswhere electrodes on the catheters are located near or adjacent eachother. Furthermore, the equivalent bipolar EGMs so derived possesscharacteristic shapes and relationships that reflect physiologic andanatomic directions which enable better contact maps by virtue of moreconsistent activation timing directions. The presence of closely spacedelectrodes also helps to characterize the substrate in the immediatevicinity (e.g., a few mm) of the catheter. The omnipolar electrogramsignal's amplitude and morphology would only be a function of the localsubstrate's electrophysiology and hence lends itself to the creation ofbetter, consistent, and more useful contact maps. Examples ofhigh-density catheters that can be used for the purpose include (but arenot limited to) the catheters shown in FIG. 2, and basket catheters likethe catheters shown in FIG. 3 and FIG. 7.

FIGS. 2A-2C show embodiments of catheters that can be used forhigh-density (HD) mapping applications. FIG. 2A illustrates oneembodiment of a catheter 10 comprising a catheter body 11 coupled to apaddle 12. The catheter body 11 can further comprise a first bodyelectrode 13 and a second body electrode 14. The paddle 12 can comprisea first spline 16, a second spline 17, a third spline 18, and a fourthspline 19 that are coupled to the catheter body 11 by a proximal coupler15 and coupled to each other by a distal connector 21 at a distal end ofthe paddle 22. In one embodiment the first spline 16 and the fourthspline 19 can be one continuous segment and the second spline 17 and thethird spline 18 can be another continuous segment. In other embodimentsthe various splines can be separate segments coupled to each other. Theplurality of splines can further comprise a varying number of electrodes20. The electrodes in the illustrated embodiment can comprise ringelectrodes evenly spaced along the splines. In other embodiments theelectrodes can be evenly or unevenly spaced and the electrodes cancomprise point or other types of electrodes. FIG. 2B illustrates anotherembodiment of a catheter 30 that can be used for HD mappingapplications. The catheter 30 can comprise a catheter body 31 coupled toa paddle 32. The catheter body 31 can further comprise a first bodyelectrode 40 and a second body electrode 41. The paddle 32 can comprisea first spline 34, a second spline 35, a third spline 36, and a fourthspline 37 that are coupled to the catheter body 31 by a proximal coupler33 and coupled to each other by a distal connector 38 at a distal end ofthe paddle 39. In one embodiment, the proximal coupler 33 can furthercomprise an electrode.

Electrode placement along splines is controlled by the good mechanicalstability of electrodes on splines. As a result, spacing along splinesis best determined not by the mapping system, but by design andmanufacturing. But spacing between splines is variable as a result ofthe forces and torques experienced as a catheter is maneuvered to adesired location. Electrodes located in spline midsections are mostvulnerable to displacement. FIG. 2C shows incorporating slender tensileelements configured to join the splines near their centers to limit themaximal displacement from one another. One means to accomplish this isto use slender mono or multifilament nylon thread or suture likematerial, fastened at the ends, and looping around splines in themiddle. A pass through a reflow oven during production allows thethreads to become incorporated into the spline's polymer insulation,securing the thread to each spline and minimizing protuberances.

FIG. 2C illustrates one embodiment of a catheter 100 using tethers tolimit the maximal spread between splines and thus enforce a moreconsistent electrode spacing when in use. The catheter 100 can comprisea catheter body 101 coupled to a paddle 102. The catheter body 101 canfurther comprise a first body electrode 103 and a second body electrode104. The paddle 102 can comprise a first spline 108, a second spline109, a third spline 110, and a fourth spline 111 that are coupled to thecatheter body 101 by a proximal coupler 105 and coupled to each other bya distal connector 112 at a distal end of the paddle 114. The paddle 102can further comprise a first support member 106 and a second supportmember 107 to limit displacement of the splines from each other. Thesesupport members can be slender tensile elements (like threads or suturematerial) that collapse during insertion of the catheter 100 into asheath. The catheters shown in FIGS. 2A, 2B, and 2C are furtherdescribed in international application no. PCT/US2014/011,940 filed 16Jan. 2014 and published in English on 24 Jul. 2014 under internationalpublication no. WO 2014/113612 (the '612 application) and U.S.provisional application No. 61/753,429, filed 16 Jan. 2013 (‘the '429application). The '612 application and the '429 applications are bothhereby incorporated by reference in their entirety as though fully setforth herein.

FIG. 3. Illustrates an embodiment of a basket catheter 50 which can beconsidered to be a 2D array of electrodes distributed over an ellipsoidsurface. The basket catheter 50 can comprise a catheter body 51 coupledto a basket 52. The basket 52 can be coupled to the catheter body with aproximal connector 53. The basket 52 can comprise a plurality of splines57, a distal coupler 55, and an irrigation tubing 56. Each of theplurality of splines 57 can comprise at least one electrode 54. In theillustrated embodiment, each of the plurality of splines comprises 8electrodes. The exact number of electrodes can be varied based on thedesired characteristics. The basket catheter shown in FIG. 3 is furtherdescribed in U.S. provisional application No. 61/936,677, filed 6 Feb.2014, which is hereby incorporated by reference as though fully setforth herein

Current techniques to estimate conduction velocity and the direction ofactivation generally rely on the precise determination of activationtimes over precise distances. The techniques to assign times to signallocations can result in predictions that are not accurate under certainconditions. The method below utilizes the fundamental concept of wavepropagation and does not rely on LAT (local activation time) detectionalgorithms. This approach is more robust and consistent. Certainextensions are also described that specialize and enhance theapplication to 2- and 3-dimensional arrangements of electrodes oncardiac surfaces. With each depolarization, the local electric fieldvector, E, sweeps out a loop like trajectory governed by anatomic andphysiologic factors adjacent to these arrangements of electrodes. Twodimensional electrode arrangements allow the resolution of E_(t), the“tangent bipole vector”, which is a useful orientation independentsignal to which wave propagation principles can be applied and can beused to introduce a scalar version of E_(t) along the unit activationdirection a, and call it E_(a). Three dimensional electrode arrangementsallow the resolution of a second equivalent bipole component of E alongthe surface normal direction denoted ii called E_(n). Finally, both 2-and 3-dimensional electrode arrangements allow determination of the Efield along the direction ŵ={circumflex over (n)}×â called E_(w) whichfor a wave traveling in direction â is a very small signal.

FIG. 4 illustrates the unit activation vector 91, wavecrest vector 92,surface normal vector 94, wavefront crest 90, and conduction velocitydirection 93. A single depolarization wavefront 90 is depicted based ona unipolar traveling wave voltage signal, φ(x,y,z,t). Propagation of thedepolarization wavefront 90 occurs from left to right in the view. Thedepolarization wavefront 90 does not have to conform to a specific shapefor the discussion within this disclosure to be valid, but a benefit canbe found from physiologic unipolar morphology.

The catheter orientation independent omnipole signals E_(n) and E_(a)possess characteristic shapes and amplitudes in normal myocardium. Thiscan be further seen in FIG. 10A. These permit more robust determinationsof EP characteristics such as electrogram amplitude, activation timing,and conduction velocity by traditional means.

The next section explains the derivation of the omnipole or “equivalentbipole” signal E_(a) using a high density catheter such as one of thecatheters 10, 30, 50 shown in FIGS. 2-3. The paddle catheter, basketcatheter, or other high density catheter is presumably maneuvered suchthat some or all adjacent electrodes lie flat on the surface/substrate.For convenience the following will use language indicating all catheterelectrodes lie on the surface (i.e. the catheter lies on the surface)but the language refers to those electrodes that do lie on the surfaceor are sufficiently close to be indistinguishable from those that do.

The E-field (E) in the plane of the surface can be calculated usingelectrode locations X and the potentials measured at the electrodes φusing the following equations (where dφ and dX have been derived from X,φ, and subtraction matrix F, as described in international applicationno. PCT/US2014/037,160 filed 7 May 2014 and published in English on 13Nov. 2014 under international publication no. WO 2014/182822 (the '822application) and U.S. provisional application No. 61/855,058, filed 7May 2013 (‘the '058 application). The '822 application and the '058applications are both hereby incorporated by reference in their entiretyas though fully set forth herein. The information is also furtherdescribed in international application no. PCT/US2015/017,576 filed 25Feb. 2015 (the '576 application) and U.S. provisional application No.61/944,426, filed 25 Feb. 2014 (‘the '426 application). The '576application and the '426 applications are both hereby incorporated byreference in their entirety as though fully set forth herein. Theequations have the same form for both 2D and 3D situations:

dφ=−(dX)^(T) ·E  (1)

E=−((dX)^(T))⁺ dVp  (2)

whereφ—vector of unipolar potentials,dφ—vector of bipolar potentials with respect to a common referenceelectrode,X—matrix of mapping system coordinates for the electrodes,dX—matrix of bipolar displacements with respect to the referenceelectrode location, andA⁺ is the Moore-Penrose generalized inverse of matrix A.However, for the 2D case where electrodes lie almost exactly in a singleplane, the resulting E-field can be constrained to that plane. This maybe done, for example, by fitting a plane to locations X, and by denotinga unit normal vector to this plane as {circumflex over (n)}, eliminatingany contribution in direction ii and thus obtainingE_(t)=E−(E·{circumflex over (n)}) {circumflex over (n)}.

FIG. 5. Illustrates one embodiment of a paddle catheter 70 showing 16electrodes and some of the sets of electrodes that can be used todetermine E_(t). In the illustrated embodiment, the paddle catheter 70can comprise four splines with each spline comprising four electrodes.Any 2D electrode set with at least three adjacent non-colinearelectrodes forms a clique and can be used for the calculations. A threeelectrode clique 71, a four electrode clique 72, and a five electrodeclique 73 is illustrated on the paddle catheter 70 in FIG. 5. The threeelectrode clique 71 can comprise electrodes D 75, two 76, and five 77.The four electrode clique 72 can comprise electrodes six 78, seven 79,ten 80, and eleven 81. The five electrode clique 73 can compriseelectrodes six 78, nine 82, ten 80, eleven 81, and fourteen 83. As canbe seen by the above illustration, the same electrode on the cathetercan be used for multiple cliques.

The local E-field at a position on the surface can be calculated fromsets of sufficient nearby electrodes (also referred to as a clique) onthe catheter as illustrated in FIG. 5. As indicated generally by dashedlines in FIG. 5, for example, a 2-dimensional clique may comprise a setof three or more electrodes (e.g., electrodes D, 5, 2) located along aplane of the catheter. When only a unipole or bipole is present, theclique can be referred to as a degenerate clique. A degenerate clique isunable to be used to determine orientation independent assessments ofdirectional quantities. A unipole degenerate clique, while orientationindependent, has no real directional information. When, for example,more than 3 electrodes are used in a clique, the bipolar signalsover-determine the 2D field, e.g. E_(t). In such an instance, where theclique has more electrodes than strictly necessary for its 2D or 3Drole, the clique is overdetermined and admits “subcliques.” Subcliquesare themselves cliques which may or may not be minimal depending on howoverdetermined the original clique was to start with and what subcliqueis being reviewed. Cliques that are not degenerate allow omnipoles andsubcliques allow a unique direct demonstration of orientationindependent sensing (OIS) superiority over traditional bipoles. OIS canbe uniformly better than bipoles in determining many EP characteristics,including amplitude, timing, conduction velocity direction andmagnitude. Although FIG. 5 only illustrates cliques comprising three(electrodes D, 5, 2) 71, four (electrodes 6, 10, 11, 7) 72, and 5(electrodes 9, 14, 11, 6, 10) 73 neighboring electrodes, the method canbe extended to other cliques with more electrodes on the catheter. Sincethe catheter is assumed to lie flat on the substrate, the full 3D vectorE at any clique is also expected to have components in the 2D tangentplane of the endocardial or epicardial surface. As a result, the termE_(t) is used to describe the component of the E-field in the tangentplane.

One method of determining the local E field is to choose one electrodefrom the clique as a reference electrode and determine n−1 bipolarpotentials (dφ) and displacements (dX) with respect to the referenceelectrode. Another method of determining the local E field is todetermine all possible distinct bipoles (n*(n−1)/2) from the clique's nelectrodes to compute dφ and dX. Determining all possible distinctbipoles can lead to a more robust determination of the E-field as itreduces “2nd order” orientation effects that result from the electrodedistribution with respect to wavefront.

Let â and w be unit vectors in the tangent plane along the activationand wavefront directions as illustrated in FIG. 4. For an ideal,homogenous wavefront, E_(t) is expected to be either parallel oranti-parallel to the activation direction (â) with very little componentalong the wavefront direction (ŵ). The scalar E_(a) (also the equivalentbipole or omnipole activation signal) can be defined using the inner ordot product as

E _(a) =E·â=E _(t) ·â  (3)

E_(a) is the equivalent bipolar EGM that would be measured on thecardiac surface if one were to place a pair of bipoles separated by 1 mmalong the activation direction. By definition, E_(a) is catheter andclique orientation independent and hence its morphology and amplitudeshould purely be a function of the local substrate. By virtue of itbeing a bipolar signal, it is also expected that it would be largelyfree of far-field artifacts and can possess a stable isoelectricbaseline.

The two signals thus resolved (E_(n) and E_(a)) are significantlyindependent of each other, opening the possibility of learning more fromlocal EGM signals. The algorithm to determine a from E_(t) will beexplained below.

The conduction velocity can be derived from the E-field using travelingwave concepts. The potential is recognized to be a function of space andtime. Propagation of a traveling wave with velocity v=(v_(x), v_(y),v_(z)) implies that the wave at time t₀ matches exactly the wave at atime t₀+t at coordinates x+v_(x)t, y+v_(y)t, and z+v_(z)t. As a result

φ(x ₀ ,y ₀ ,z ₀ ,t ₀)=φ(x ₀ +v _(x) t,y ₀ +v _(y) t,z ₀ +v _(z) t,t ₀+t)  (4)

for all initial times and locations t₀, x₀, y₀, z₀ and for all times t.Taking the total derivative of both sides of the above equation withrespect to time leads to

$0 = {{\frac{\partial\varphi}{\partial x}v_{x}} + {\frac{\partial\varphi}{\partial y}v_{y}} + {\frac{\partial\varphi}{\partial z}v_{Z}} + \frac{\partial\varphi}{\partial t}}$

which we note is equivalent to

0=∇φ≤v+{dot over (φ)}  (5)

where v is a vector representing cardiac conduction velocity.Recognizing that E=−∇φ and that only the component of E-field in thetangent plane contributes to the inner product, we get

E _(t) ·v={dot over (φ)}  (6)

E _(a)(â·v)=φ  (7)

The conduction velocity vector v can then expressed as

$\begin{matrix}{\nu = {\frac{\overset{.}{\varphi}}{E_{a}}\hat{a}}} & (8)\end{matrix}$

The magnitude of conduction velocity, a presumed constant during localdepolarization, is recognized to be the ratio of the time derivative tothe spatial derivative along the direction of activation in the tangentplane of the potential. It is then expected that under ideal conditions,the morphology of E_(a) would be similar to that of {dot over (φ)} withthe only difference being a scale factor which would be the velocitymagnitude. The activation direction (â) can be determined to be thedirection in the tangent plane that results in the maximum correlationbetween {dot over (φ)}(t) and E_(a)(t). Although the expression (8)above holds in principle at every time point during local depolarizationand location within the clique, when signal levels are sufficientlysmall or isoelectric, the ratio of {dot over (φ)} to E_(a) cannot bemeaningfully determined.

The analysis can be expected to be more robust when the electrodes thatform a clique are in good contact with the surface. This can be checkedand enforced a priori using some or all of the criteria below. Thecriteria to check whether a clique is in good contact with the surfacecan be applied together or separately as determined by the user orprocess. Automatic application of the first six criteria can form animportant component of the disclosure as getting uniform contact of allelectrodes is generally difficult for any catheter, particularly so forsmall basket catheters.

The first criteria looks at the angular deviation between a 3D mappingsystems determined surface normal near the clique and the normal to theplane that best fits the electrodes on the clique and determines whetherthey are below a threshold. The second criteria looks at the angulardeviation between the normal corresponding to the clique of interest andthe normal corresponding to the neighboring cliques and determineswhether they are below a threshold. The third criteria looks at thedistance between the electrode locations that form the clique and thesurface and determines whether they are below a threshold. In oneembodiment, the second criteria further includes ensuring that the localcurvature is not above a threshold. The fourth criteria looks at theamplitudes of the unipolar signals obtained from the electrodes on theclique and determines whether they exceed the noise level and are withina typical range. The fifth criteria looks at the morphologies of theunipolar signals obtained from the electrodes on the clique anddetermines whether they are typical (e.g. modest upstroke followed by adominant down deflection and fairly prompt return) and reasonablyconsistent. In another embodiment, an additional criteria can be used bylooking at the morphologies of {dot over (φ)} to determine whether theyare typical and reasonably consistent. Unipolar signals {dot over(φ)}(t) can also sufficiently resemble omnipole signal −E_(n)(t). Thesixth criteria looks at the amplitudes, shapes, and morphologies ofE_(t), and E_(a) obtained from the clique and determines whether theyare typical. Omnipole signal E_(a)(t) can sufficiently resemble {dotover (φ)}(t). The seventh criteria looks at the visual cues for goodcontact such as fluoro, ICE, etc. as well as tactile sensations andmaneuvering history on the part of a catheter operator. While sevencriteria are listed herein to check whether a clique is in good contactwith the surface, not all seven of the criteria listed have to be usedto make that determination. Further, other criteria can also be used todetermine whether a clique has made good contact with a surface.

Conduction velocity once derived can be displayed with a 3D mappingsystem on the chamber geometry using, for example, arrows, with thedirection of the arrow indicating the activation direction and thecolor, length, or width of the arrow showing the magnitude. In anotherembodiment an interpolated color map can also be used to displayconduction velocity magnitude with or without arrows of uniform lengthshowing the direction. In another embodiment, conduction velocity vectormaps can also be coupled with voltage amplitude or LAT maps. Generally,the display is updated immediately following each local depolarizationand persisting or gradually fading out until the next localdepolarization. Finally, some or all isochrones may be displayed ascurved lines on the cardiac surface, for instance at specific intervalssince the start of depolarization such as 0, 10, 20, and 30 ms. Thisreduces visual clutter and allows a more interpretable superposition ofconduction velocity arrows. In another embodiment, some or allisochrones may be displayed as curved lines on the cardiac surface, forinstance at specific intervals since the start of depolarization such as0, 20, 40, and 60 ms.

As can be readily appreciated from equations 1 and 2 listed above, it isimportant to have reasonably accurate electrode displacements (dX) andelectrode positions (X) to judge contact and the local surface tangentplane so as to portray the signals and resulting EP characteristicsincluding conduction velocity accurately. It has been suggested thatimpedance based mapping system locations are more robustly determinedfrom tip or circumferential ring electrodes than from small surface areaelectrodes on portions of a catheter shaft. Nevertheless, the issue canremain significant in catheter designs with small ring electrodes onflexible splines. Small electrodes, owing to their highelectrode-electrolyte impedance can be difficult to locateaccurately—they are more susceptible to artifact and can be biasedtoward the system reference “belly patch” electrode. Compensationalgorithms can be used to correct for the positions. However, they relyon a priori knowledge of the construction and inter-electrode distances.Flexible splines can deform, bunch up, or become separated (splayed) invivo under certain conditions resulting in important deviations fromtheir nominal design. When that happens, the compensation algorithmsreferred to above may not be able to effectively correct electrodelocation errors. Means to prevent the deformations, bunching, andseparation of catheter splines and electrodes from becoming severeenough to significantly disturb assessments of EP characteristics arealso disclosed above in relation to FIG. 2C.

FIG. 6 illustrates a flowchart showing a step-by-step approach toacquire, determine, and output orientation independent information. Themethod illustrated in the flowchart can comprise the following steps:

At step 130 acquire electrophysiology signals from a plurality ofelectrodes.

At step 132 determine the location of the plurality of electrodes instep 130.

At step 134 determine whether the plurality of electrodes are on or nearthe target surface.

At step 136 form cliques from the electrodes that fit within definedcharacteristics for inclusion in cliques.

At step 138 process the electrophysiology signals to determine E_(n),E_(a), E_(t), conduction velocity, and other orientation independentcharacteristics such as amplitude or timing.

At step 140 output the derived information to a display.

Helical basket catheters have been proposed as a means to achieve moreuniform coverage of electrodes over the extent of a basket. This can bea desirable characteristic for this disclosure on its own, but also forthe increased stiffness (and thus resistance to displacement) thatresults. Increased stiffness can allow for reliance on the spacing asdetermined by design and manufacturing rather than the mapping systemlocation for each electrode.

FIG. 7 illustrates a helical catheter design of a catheter 120 withnon-uniform electrode spacing along splines but achieves a nearlyuniform electrode dispersal over the outer surface of the basket. Eachpoint 121 in the figure represents an electrode. The catheterillustrated in FIG. 7 is further described in U.S. application Ser. No.13/790,110, filed 8 Mar. 2014, (the '110 application) which is herebyincorporated by reference as though fully set forth herein.

Beam buckling theory suggests compliance goes as the length dimensionsquared so half the length translates to 4 times stiffer. With smallsize, then, come the benefits of: (a) interelectrode spacing moreconsistent under varying use conditions, (b) more dense sampling andthus better spatial resolution, and (c) the capacity to be maneuveredinto full contact positions and orientations.

As discussed earlier, conventional mapping techniques suffer from bipoleorientation induced amplitude and morphology uncertainty which alsoadversely affects activation timing. Challenging arrhythmias in clinicalEP today may involve features such as channels with low amplitudes andslow conduction that are only of the order of 5 mm in width. Detailedmaps are often not required over an entire cardiac chamber but confinedto certain locations where pathology often appears or other diagnostictests such as surface ECGs, ultrasound, MRI, or even basic EP cathetersignals indicate. What is important is that the information reliablyreflect the state of the myocardium locally and that it do so withadequate resolution.

The algorithm discussed in the invention can be used to derive localE-fields (including E and E_(t)), and equivalent bipolar signals (E_(n)and E_(a)) with orientation independent amplitudes and reliablemorphology/timing, and instantaneous conduction velocity vectors. Suchcharacterization can permit improved maps of substrate amplitude (usingE_(n), E_(a), or measures of E or E_(t) loop size such as maximaldimension also known as E_(span)), activation times (LAT), conductionvelocity (magnitude and direction), as well as an index of inhomogeneousconduction derived from E_(w) or the eccentricity of E_(t). Bipolar-likeomnipole signals of consistent morphology may be understood from thefundamentals of cell depolarization and unipolar EGM signals when inproximity to active tissue.

One or more of these characteristics can also enable clinicians toperform more reliable scar border delineation (known to contribute to VTand other arrhythmias). Also, local determinations of low amplitudeand/or slow conduction velocity can help identify critical pathways suchas isthmuses for arrhythmias that are amenable to ablation therapy. Morereliable EGM amplitudes and morphologies can also allow better measuresof EGM reduction measures, lesion characterization, or the localassessment of conduction velocity as a critical isthmus is affected or alesion gap approached.

OIS technology can also be utilized with implanted medical devices.Implanted medical devices responsible for rhythm discriminationcurrently rely primarily on depolarization event timing. Timing alonehowever can fail to distinguish between important rhythms as the timesof occurrence can be similar, and multi-chamber algorithms are notsufficiently specific. The application of OIS to an implanted device'scatheter or lead can establish a baseline direction and speed (using OIScharacterizations) for healthy rhythms.

Implanted devices already perform elementary mapping system functions,but with OIS technology as discussed herein, can better track the numberand degree of abnormality of beats and can group them by similarity indetection criteria. For example, a non-physiologic heart rate increasetypically would cause the conduction velocity to decrease, while aphysiologic cause for heart rate increase, like exercise, would notresult in a decrease in conduction velocity. Hence the decision to treatthis tachycardia can be based not only on changes in heart rate andother traditional ICD metrics such as timing but based on noting theconduction velocity vector's direction and magnitude are consistent witha VT. Some of the detection criteria that can be used by the implanteddevice can include combinations of rate, number consecutive abnormalbeats, frequency “x of y beats”, etc.

Observations from one or more sites on implanted leads can also be usedto track rate or ischemia induced functional block occurrences withgreater accuracy than inferences drawn from timing changes. This in turncan enable patient or health care provider alerts to potential problemswith brady or tachy arrhythmias before deciding on treatments withpacing or cardioversion shocks.

FIG. 8 illustrates a paddle catheter 400 and the cliques used for thecomputations discussed herein. The paddle catheter 400 can comprise afirst spline 401, a second spline 402, a third spline 403, and a fourthspline 404. Each of the splines can comprise four electrodes. For thepurpose of validation, cliques comprising four electrodes (two from eachpair of adjacent splines as seen in FIG. 8 can be used. In someinstances some of the rectangular cliques can be considered to not be incontact with the cardiac surface.

The determination of whether a clique can be considered to be in contactwith the cardiac surface can be accomplished in a variety of ways. Thereare a variety of methods that can be used to determine whether a highquality OIS signal is present.

In one method, the peak-to-peak amplitude ratio of E_(w)/E_(span) can beused. A low ratio of the peak-to-peak amplitudes of E_(w)/E_(span) canlead to a finding of a high quality OIS signal. E_(w) is the signal thatremains when E_(n) and E_(a) are accounted for and, for an idealhomogeneous wavefront traveling linearly with ideal OIS coordinatesshould be zero. E_(span) is a term to describe what is the peak-to-peakequivalent amplitude for the entire E field loop. E_(span) is themaximum over all of the depolarization's E field point pairs of|E_(i)−E_(j)| at time points i and j. Importantly, it does not requireideal wavefronts or coordinates and will be greater than or equal toE_(a) peak-to-peak and E_(n) peak-to-peak.

In another method, the cross correlation lags between E_(a) and {dotover (φ)} can be used. A low cross correlation lag between E_(a) and{dot over (φ)} can lead to a finding of a high quality OIS signal. Inone embodiment, a low cross correlation lag can be defined as typicallyless than 5 ms for a catheter designs with 1-4 mm between electrodes. Inother embodiments, a different value can be used to define a low crosscorrelation lag. In another method, the conduction velocity can be usedto determine the OIS signal quality. A physiologically plausibleconduction velocity determination can be used to determine the signalquality at a given location. In one embodiment, a conduction velocity ofhealthy tissue can be set in the range of 0.4-1.4 mm/ms and theconduction velocity in or near scar tissue can be set in the range of0.05-1.0 mm/ms. In yet other embodiments other velocities can be used bythe system to determine the quality of any OIS signals. A user of thesystem can further set a different value for the system to use todetermine a signal quality.

In yet another method, the amplitude of a unipolar signal can be used.In on embodiment, a unipolar signal amplitude can be determined to beadequate to give a quality OIS signal can be set as 0.5-15.0 mV inhealthy tissue. In another method, the unipolar morphology can be usedto determine the quality of an OIS signal. A plausible unipolarmorphology can be determined by looking for a unipolar morphology thatcomprises a main portion that either contains a small to moderate sizedupward deflection followed by a moderate to large downward deflection ora unipolar morphology that comprises a moderate to large downward one.In another method, the cross correlation between clique unipoles can beused. A good maximal cross correlation between clique unipoles cansuggest that the clique unipoles reflect a locally homogeneousassessment of conduction.

In yet another method, a unipolar temporal dispersion over the cliquecan be used to determine a high quality OIS signal. A unipolar temporaldispersion over the clique, in the range of 1-6 ms for a catheter designwith 1-4 mm between electrodes can show a high quality OIS signal. Theunipolar temporal dispersion may be determined by conventional dV/dtthreshold crossing techniques or by maximal cross correlations. Inanother method, the derived OIS omnipole signals can be compared toidealized E_(n) and E_(a) signals. The closer the OIS signal is to theidealized values, the better the OIS signal. A comparative value can beset within the system or can be set by a user to state the amount ofresemblance desired to determine whether a high quality OIS signal ispresent. In another method, the loop-derived {circumflex over (n)} canbe compared to the surface normal from an electroanatomical mappingsystem. In one embodiment, a good match between a NavX mapping systemdetermined {circumflex over (n)} direction and a loop derived{circumflex over (n)} direction can show a high quality OIS signal. TheNavX mapping system can determine an {circumflex over (n)} directionfrom surface shape and catheter clique electrode locations. In yetanother embodiment, electrogram signals with isoelectric intervals canbe used to determine whether a high quality OIS signal is present. Anisoelectric interval with no baseline drift and no large offset over anOIS analysis interval can be used to determine a high quality OISsignal. In one embodiment the OIS analysis interval can comprise 20-80ms. In other embodiments, the OIS analysis interval can be longer orshorter or of an interval chosen by a user of the system.

There are also a variety of methods that can be used to determinewhether a poor quality OIS signal is present. In one method, themagnitude of the conduction velocity can be used to determine whether apoor quality OIS signal is present. If the conduction velocitymagnitudes are larger than would otherwise be expected the system oruser can determine that poor quality OIS signals are present. Abnormallylarge conduction velocity magnitudes can be caused by far field signalssince these can often produce very small peak-to-peak E_(a) values. Inone embodiment, if the conduction velocity magnitude is greater than 2-3mm/ms a poor quality OIS signal can be determined. In other embodimentsother values for excessively large conduction velocity magnitudes can beused. In another method, a unipolar EGM signal can be analyzed todetermine whether a poor quality OIS signal is present. A unipolar EGMsignal that shows a prominent positive deflection persisting for 60-80or more ms following depolarization can indicate an injury currentcomponent to the unipolar EGM signals. In another method, a saturationof one or more EGM channels can reflect pacing polarization andamplifier recovery. This can also lead to a finding of a poor qualityOIS signal.

In yet another embodiment, several different methods can be used todetermine whether far field artifact could be causing low qualityindices. The methods to determine whether far field artifact is causinglow quality indices could include one or more of: “beats” where thetentative detections on all unipolar clique electrodes are virtuallysimultaneous; if the timing of E_(n) and/or E_(a) in the atria issufficiently close to that of the surface QRS and thus suggests aprobable ventricular unipolar artifact; and at least one small E-fieldloop. A small E-field loop can be caused by far field signals thatresult in E-field loops with very small E_(span). In one embodiment,when the E_(span) value is less than 0.5 mV/mm the system or user candetermine that far field artifact is causing low quality indices.

FIG. 9 shows the loop trajectory of vector E_(t) 420 in the tangentplane over 100 ms of the cardiac cycle when the catheter cliqueelectrodes see atrial depolarization action. If the wavefront passes theclique electrodes progressing uniformly in a homogeneous medium (as seenin FIG. 4), then vector E_(t) 420 should comprise voltage swings along adominant axis aligned with the activation direction. The activationdirection, calculated using the method described in the previous sectionis shown using the arrow. The plot shows the trajectory of vector E_(t)420 over a single beat. The tail of the vector is anchored at theisoelectric origin and the plurality of dots 421 indicate the path ofthe head of the E field vector. The vector sweeps a loop around theorigin with maximum and minimum excursions along the activationdirection (indicated with the arrow).

FIG. 10A shows the EGM's, their time derivative {dot over (φ)} (phi-dot)and the “equivalent bipole” E_(a) plotted as a function of time for twobeats. Note that the morphology and amplitude of the signal isconsistent from one beat to the other and that the far-field ventricularsignal that we see in the unipolar EGM's is largely absent. Theexemplary E_(a) has a negative deflection followed by a prominent sharppositive deflection. Also, its amplitude is expected to be solely afunction of the substrate that is being investigated (and not catheteror bipole orientation). FIG. 10B shows the stylized shape of anexemplary E_(a) with a negative deflection followed by a sharp positivedeflection.

Due to various factors that contribute to non-ideal conditions,including finite spatial separation of electrodes, the morphologies of{dot over (φ)} and E_(a) do not match exactly but they are very close toproportional. As a result the ratio (velocity magnitude in idealconditions) is not uniform over the time interval of the beat. Also,when one or both of {dot over (φ)} and E_(a) of Equation 8 approacheszero, the algorithm fails to produce meaningful results. Under idealconditions, {dot over (φ)} and E_(a) would tend to zero at the sameinstant in time and in the limit when they both tend to zero the ratiocould be meaningfully evaluated to be the conduction velocity magnitude.In practice zero crossings of the denominator and numerator play havocwith this ratio.

The practical limitations can be overcome by realizing that a classicunipolar signal recorded at an electrode includes contributions fromdepolarizing tissue upstream and downstream of the electrode location.The information about depolarizing tissue immediately under theelectrode is contained within the region of maximal −dv/dt, peaknegative deflection, and the immediate up stroke following the unipolarpeak negative. This corresponds to the region contained within the peaknegative and the subsequent positive peak in {dot over (φ)} and E_(a).This region can be seen as time interval 481 in FIG. 11. Conductionvelocity is calculated using information from the signals within thisregion.

Listed below are some practical ways to calculate the velocity ofactivation or propagation. One way is to calculate the velocity as theratio of the peak-to-peak values of {dot over (φ)} and E_(a). Theconduction velocity estimations shown in this section have beenevaluated using this method. An equivalent mathematical way to representa ratio of peak-to-peak values is shown with definite integrals below.

$\begin{matrix}{v = \frac{\int_{t_{a}}^{t_{b}}{\frac{d\overset{.}{\varphi}}{dt}{dt}^{\prime}}}{\int_{t_{a}}^{t_{b}}{\frac{dE_{a}}{dt}{dt}^{\prime}}}} & (12)\end{matrix}$

In another embodiment the conduction velocity can be calculated byapplying different weights to the information contained within theinterval (t_(a)<t′<t_(b)) as follows

$\begin{matrix}{v = \frac{\int_{t_{a}}^{t_{b}}{w\frac{d\overset{.}{\varphi}}{dt}{dt}^{\prime}}}{\int_{t_{a}}^{t_{b}}{w\frac{dE_{a}}{dt}{dt}^{\prime}}}} & (13)\end{matrix}$

where w(t) is a weighting function. The weighting function can be usedto ensure that more importance is given to certain regions within thetime interval as shown in FIG. 12 and discussed below.

FIG. 11 illustrates a plot showing the time interval (from a to b) 481that holds the most information about depolarizing tissue under aparticular clique of electrodes. This generally corresponds to timesaround when the unipolar voltage is most negative which is when theinward current of depolarization is maximum under the electrodes of theclique. This introduces a practical and improved means to derivevelocity from local {dot over (φ)} and E_(a) signals.

FIG. 12 depicts a weighting function w vs. time. W 491 is shown betweentime t_(a) 493 and time t_(b) 495. In this illustration w is chosen toensure more importance is given to the region corresponding to thezero-crossing of E_(a) following its pk-neg.

In some embodiments, determining the activation direction from the Efield loop data can be overly sensitive to data taken when the loop issmall and nearly isoelectric. OIS signals and derived quantities mayreflect artifacts due to filtering, offsets, far field effects, orwaveform complexity when good information also exists. The artifacts canbe minimized by weighting the loop points in calculations, includingactivation direction cross correlation, not equally by time, butproportional to, or as a monotonic function of, |E(t)| or |d/dt(E(t))|as seen in FIG. 13. This can ensure that the E field data points thatlie close to the origin or are changing slower than the depolarization,as seen in FIG. 13, are given less weight. Only the major deflections,which provide the necessary and key information about the underlyingsubstrate, are then used for deriving OIS quantities, including the OIScoordinate frame ({circumflex over (n)}, â, ŵ) and omnipole signalsE_(n) and E_(a). This can concentrate OIS results on the informationcontaining part of the loop when the E field changes rapidly. Thisweighting can further be used in deriving OIS coordinate directionsentirely from the E field loop, which could also lead to more accuratedetermination of E_(n) peak-to-peak, E_(a) peak-to-peak, and conductionvelocity magnitude. In another embodiment, when d/dt(E_(t)) isdetermined to be too high, this can be due to artifacts and can be usedin addition to the set of OIS quality criteria discussed above.

FIG. 13 illustrates an E-field loop showing regions of large and small|d/dt(E(t))|. The points 440 are EGM derived E-field points equallyspaced in time. As discussed above, closely spaced points contain littleinformation and contain artifacts that can affect OIS derived signalsand EP characteristics. The area around the origin 441 has a small|d/dt(E(t))|, while the area with a large |d/dt(E(t))| 443 correspondsto strong EGM signal amplitudes and deflections. The area with a large|d/dt(E(t))| is of more interest. As a result, in one embodiment, thoseareas with a small |d/dt(E(t))| can be removed or deemphasized.

In another embodiment, the loop points can also be weighted based on themagnitude of the E-field (norm(E) or |E|) which is the distance from theisoelectric origin. FIGS. 14A and 14B show the tangent E-field looppoints before and after weighting based on the method described herein.FIG. 14A illustrates the tangent E-field loop 451 before weighting. FIG.14B illustrates the tangent E-field loop 455 after weighting the looppoints 457 based on the norm of the E-field. As can be seen in thecomparison of FIGS. 14A and 14B, the part of the loop that contains themost useful EP information is accentuated and hence more meaningful OIScharacteristics can be obtained from the weighted loop.

FIGS. 15A and 15B show the magnitude of conduction velocity estimatedfor successive beats on the RA septal wall for two different squarecliques. FIG. 15A shows the magnitude of the conduction velocity forclique 6 and FIG. 15B shows the magnitude of the conduction velocity forclique 8. The velocity magnitude was estimated by taking the ratio ofthe peak-to-peak values of {dot over (φ)} and E_(a). The beat-to-beatvariation in conduction velocity magnitude is minimal and the values ofaround 1.3 mm/ms are roughly what was expected. Conduction velocitymagnitude and activation direction (unit vector) estimated forsuccessive beats from the two adjacent cliques were as follows.

-   -   Clique #6        -   Velocity magnitude=1.35±0.06 mm/ms        -   Activation direction=(0.12, −0.91, 0.40)    -   Clique #8        -   Velocity magnitude=1.29±0.05 mm/ms        -   Activation direction=(0.10, −0.80, 0.58)

The activation direction and velocity calculated were similar andconsistent with expected results in atrial tissue.

A split tip OIS catheter is also suitable for bipolar pacing in a mannerthat is much more tip localized than the conventional D-2 bipolar pacingand free of the concern over variable locational of capture (andvariable thresholds) that can occur when the ring (and not the tip)captures myocardium. This is a great advantage when, for example, pacingis being done to establish lesion efficacy. The alternative, unipolarpacing, involves a distant electrode and thus is responsible for a largepacing artifact that complicates use of pacing for assessing blocks. Thebasic idea is that pacing is accomplished by assigning alternatingpolarities to the four tip electrodes. This may be accomplished bycircuit elements such that the four electrograms and mapping systempositions remain distinct and yet the tip appears as a “crossed bipole”from the standpoint of pacing. Alternatively this may be done byemploying the stimulator, devoting two simultaneous channels to the fourelectrodes.

With each local depolarization, a new conduction velocity vector may begenerated. The system can be configured to display various informationincluding oriented arrow icons, Matlab quiver-like plots, and ripplemaps. The system can further have the option to control the persistenceof these direction and/or magnitude renderings. In one embodiment, thedefault process is to update immediately with each new localdepolarization (that meets criteria for a depolarization).

Updates that visually replace prior visual assessments are sometimespreferred over cumulative multi-beat maps because if there is onlymodest movement of the catheter between repeated similar beats, the mapwill become cluttered with such representations. As a result, it can bebeneficial to include a spatial density criterion (like that currentlyavailable with traditional mapping systems). New representation pointswould be added if none are within say 2 mm of previous points (and fromthe same mapped rhythm if that is distinguished). If old points liewithin 2 mm of a new point, the new points can delete or hide oldpoints. Particularly when playing back recorded segments and focus is ona region of interest where a multi-electrode mapping catheter is, thesystem can hide/delete prior representations at points in favor of themost recent cardiac cycle's representation since play back began.

In another embodiment, a variable persistence can be given to the pointrepresentations based on, a given number of milliseconds duration andobserved during slow playback. The visual representations at points cancome into existence and disappear in a manner that (similar to apropagation map available on the EnSite Velocity mapping system)suggests the wavefront itself (a region of typically 0.5-1 cm or so widethat encompasses the 5-10 ms or so of primary depolarization current andEGM generation). This can benefit the system by removing clutter andfocusing attention on immediate events.

Transmural RF ablation possesses certain EGM characteristics which areexploitable by an orientation independent, OIS catheter electrode designand software. In particular, the unipolar signal (which to a firstapproximation is just a polarity inverted E_(n) signal) may change froman rS pattern preablation to an r′ pattern afterward. As a result, E canchange from a nice dominant upward deflection to a smaller downwarddeflection, perhaps a downward deflection that was present previously,but now appears minor in comparison with the upward deflection. This canreflect the fact that activation no longer propagates through theelectrode clique but halts as it approaches.

While some implementations require a surface normal direction,{circumflex over (n)}, to be supplied by a 3D mapping system's surfacegeometry model (based on the nearest surface point to a clique) thisimplementation can be less reliable in some circumstances. In oneinstance, using data from a 3D mapping system's surface geometry modelcan be less reliable when a cardiac surface curvature is high and thusimperfect surface models and small clique position errors can stronglyinfluence the resulting {circumflex over (n)}. The E field loop andtraveling wave approach of OIS, however, can be used to generate{circumflex over (n)} and the other two OIS coordinates, â and ŵ, fromEGMs alone. As a result, a live surface normal display can bedetermined. Such a surface normal can be a valuable reflection ofcatheter contact and wall distension and can even provide more detailedsurface geometry models in the face of highly curved structures andrespiratory or cardiac motion artifacts.

FIG. 16 is a flow diagram outlining the steps for obtaining an OIScoordinate frame.

Step 501 comprises determining the local 3D electric field loop in thebody or mapping system's coordinate frame. This step comprises havingone or more electrode cliques on the cardiac surface and using a 3Dmapping system to provide positions of electrodes comprising the cliqueand unipolar voltages obtained from the electrodes. From thisinformation the 3D electric field loop can be determined.

Step 503 comprises matched filtering of all unipolar signals, catheterbipoles, and the resulting 3D E field loop. In another embodiment, forthe purpose of OIS coordinate frame determinations and conductionvelocity and activation direction, low or band pass filtering can beemployed to create a more elliptical E field loop and thereby allow moreconsistent OIS coordinates as well as conduction velocity and activationdirection determinations. Band pass filtering of 2-50 Hz can providerobust estimates of OIS coordinates, conduction velocity, and activationdirection. In yet another embodiment, wideband filtering of E(t), e.g.1-300 Hz, can be maintained for generating OIS signals E_(n), E_(a), andE_(w) by the inner product of E(t) with {circumflex over (n)}, â, and ŵrespectively to preserve EGM detail. In other embodiments, the filteringin step 503 can be performed in a different order than that shown inFIG. 16.

After step 503, there are two possible methods for determining â,{circumflex over (n)}, and ŵ. If the system or user desires to first useŵ then proceed to step 505. If the system or user desires to use â and{circumflex over (n)} first, then proceed to step 525.

Step 505 comprises creating a zero mean version of E(t) over thedepolarization interval.

Step 507 comprises computing at each time point Ė=dE/dt(t).

Step 509 comprises computing an initial estimate of ŵ from the crossproduct of E and Ė at each time point.

Step 511 comprises averaging or weighted averaging the initial ŵestimates over the depolarization interval for a best estimate of ŵ.

After ŵ has been estimated from step 511, the method next performs a 1-Dsearch over angles θ for â and {circumflex over (n)} since â and{circumflex over (n)} have a proscribed 90 degree relationship to eachother and both are perpendicular to ŵ. Only a half circle, θ(0-180degrees), has to be searched as opposing directions will yield thenegative in terms of match scores. A search can be performed on asuitably defined grid spacing. In one embodiment, every 2-3 degrees, fora total of only 60-90 evaluations. In other embodiments, other gridspacing can be defined by the system or user. Iterative searchtechniques may also be used but care can be taken to avoid local minima.

Step 515 comprises choosing the corresponding if from the cross productâ(θ)×ŵ(θ) for every â(θ).

Step 519 comprises computing a composite match score for how well {dotover (φ)} matches E_(a)(θ)=E·â(θ) (using an inner product) and how well−φ matches E_(n)(θ)=E·{circumflex over (n)}(θ) having determined{circumflex over (n)} from above.

Step 521 comprises choosing the best θ and thus the best â and{circumflex over (n)} from the previous steps.

In another embodiment, the method can skip computing Ė from step 507 andcan instead perform a single cross product from a time point i with asizable |E(t_(i))|. This can be performed by lettingA(t)=E(t)−mean(E(t)) be a zero mean version of the 3D E fieldtrajectory. If A is assumed to be a 3×n matrix, form (1/n)*A*A^(T) (thisis a 3×3 positive definite covariance matrix). The SVD of this willyield singular values and vectors. The vector associated with the leastsingular value is ŵ (plus or minus a sign). Then check the loop'sdirection. The positive direction of ŵ “goes with the thumb using theright hand rule on the loop” and using the vector cross product betweenA(t_(i)) and A(t_(i+1))−A(t_(i)), ŵ's direction may be determined.

In another embodiment, the cross product or angular momentum can be usedto determine ŵ. Let A(t)=E(t)−mean(E(t)). Over the loop points, computethe average cross product over the n time points A×{dot over (A)} fromthe point-wise in time cross product of A(t_(i)) with its timederivative {dot over (A)}(t_(i)). Positive ŵ will be a normalizedversion of this vector. In another embodiment, the loop points can beweighted as discussed above and the average cross product computed asjust described.

If the system or user desires to use â and {circumflex over (n)} first,the method proceeds from step 503 to step 525 and conducts either a 3degree of freedom search to jointly solve for â and {circumflex over(n)} or begins with a 2D search over angles θ and ψ for either â or{circumflex over (n)}. Only a hemisphere needs to be searched asopposing directions will yield the negative in terms of match scores.The search can be conducted on a defined grid spacing. Althoughincrements of 2-3 degrees on latitude and longitude can work, this canlead to inefficient results as near the hemisphere's pole evaluationsare much closer than 2-3 degrees. In one embodiment, a method employingsome 10-20 fold fewer grid points can be used. Briefly, this uses anapproximate solution to what is known as the ThompsonProblem—distributing points evenly on a sphere. The approximate solutionconstructs lines of latitude, choosing points on successive linesrotated by π(1−φ⁻³) radians where φ≅1.62. This method is more fullydescribed in the '110 application, which is incorporated by referenceabove. Having determined â or {circumflex over (n)}, the other may befound with a 1D semicircular search. Iterative search techniques canalso be used but care taken to avoid local minima.

Step 525 comprises computing a composite match score for both how well{dot over (φ)} matches the inner product of E and â and −φ matches theinner product of E and {circumflex over (n)}.

Step 529 comprises choosing the best pair of â and {circumflex over(n)}.

Step 531 comprises determining ŵ by the right hand rule and crossproduct ŵ={circumflex over (n)}×â.

In other embodiments, the method or system can proceed down both pathssimultaneously and compare those results to determine the better fit.Whether proceeding down the path of using ŵ first, using {circumflexover (n)} and â first, or using both combined, the method then proceedsto step 535 to determine the standard final OIS information.

Step 535 comprises using the inner product of OIS coordinate directionswith E field to compute the OIS omnipole signals E_(n), E_(a), andE_(w). As discussed above, in one embodiment, the E-field from whichomnipole signals are derived can be wide band filtered once the OIScoordinate frame has been determined from a low pass filtered E-field.

Step 537 comprises computing amplitudes from the omnipole signals. Inone embodiment, the amplitudes are denoted V_(pp) for peak-to-peakvoltage and local activation timing denoted LAT.

Step 539 comprises computing the conduction velocity vector v whichconsists of the conduction velocity magnitude or speed (from theomnipole signals) times the activation direction â.

FIG. 17 illustrates an example of an E-field loop 601 and OIScoordinates. The 3D mapping system supplied a surface normal {circumflexover (n)} 603. The traditionally derived â 605 and traditionally derivedŵ 607 are determined by a process similar to that described in step 515.A loop derived OIS coordinate direction {circumflex over (n)} 609, aloop derived OIS coordinate direction â 611, and a loop derived OIScoordinate direction ŵ 613 are also shown in FIG. 17. In the illustratedembodiment, only minor readjustments were made to the coordinate frame.This minor adjustment reflects a high quality system supplied{circumflex over (n)}.

A loop derived surface normal, {circumflex over (n)}, opens up a numberof potentially useful applications relating to cardiac EP mapping. Oneof the applications is assessing the adequacy of the existing localsurface geometry model. A discrepancy between the derived informationand the existing local surface geometry model can suggest additionalgeometry model acquisition is needed or in one embodiment can beautomatically triggered. Another application is detecting a catheterforce related surface distension. The catheter force related surfacedistension can be useful in the absence of a force sensor and can alsobe useful to suggest that the underlying geometry model has beentemporarily altered. Another application of a loop derived surfacenormal is assessing the adequacy of local surface contact. Assessing theadequacy of local surface contact can benefit ablation formation and canalso be used to reflect respiration and cardiac related motions that maynot be well rendered by an existing 3D mapping system. Anotherapplication is allowing for a more robust surface geometry modeling inareas of highly curved cardiac structures and respiratory motion whereother respiratory compensation may not always be effective atsuppressing artifact and positional uncertainty. The above method canallow a user or system to recognize the situations described as themethod responds in meaningful and reproducible ways as an OIS capablecatheter is maneuvered throughout a vasculature or other body cavity ororgan.

FIGS. 18A and 18B illustrate the application described above ofdetecting a catheter force related surface distension through adetermination of the surface normal, {circumflex over (n)}. {circumflexover (n)} is of interest itself to help with catheter positioning and toindicate the adequacy of a 3D mapping system surface geometry. It mayalso provide a real-time assessment of catheter force related distentionof the endocardial or epicardial surface. This can be of particular usein the atria. FIG. 18A illustrates a catheter 651 placed at an initialcontact point 653 of a myocardial wall 655. The catheter 651 isillustrated making contact with the myocardial wall 655, but notsignificantly distorting the shape of the myocardial wall 655. As aresult, the surface normal 657 from both loop based means describedabove, and a 3D mapping system agree and are shown as {circumflex over(n)}. FIG. 18B illustrates the catheter 651 being deflected and pushedinto the myocardial wall 655. The catheter 651 is distending theendocardial surface from the original myocardial wall location 661 to adistended myocardial wall location 663. The 3D mapping system suppliessurface normal 657 is the same as in FIG. 18A. The catheter clique'scenter however is now more accurately placed at a location between theinitial contact point 653 and a second myocardial wall point 665. Aproper surface normal 667, as determined through the above loop basedmethod, is shown. By determining and using the proper surface normal 667the system enables OIS signals E_(n), E_(a), and E_(w) to be correctlyresolved and thus the other results at the bottom of FIG. 16 can becorrectly obtained. Further, the discrepancy between 3D mapping systemsupplied surface normal 657 and the proper surface normal 667 indicatesan important surface distension. This surface distension can beundetectable using a standard 3D mapping system and can also often beunrecognizable on fluoro because of view angles, contrast, and shapespresent in the fluoro system. Further, this can give a live {circumflexover (n)} display a potential role in lesion monitoring. A live displayresponding to force and local distension/deformation of the atrial wallcan be used to enhance RF lesion quality if observed characteristicresponses are seen in response to variations in tip deflection. One suchcharacteristic can be a good degree of contact with the surface targetedfor ablation. Surface normal information can inform a user of adequatecontact and thus help to provide a sufficiently complete map geometry aswell as static multi-beat maps. As geometries may change during aprocedure for real or artifact reasons, a recent discrepancy between anOIS loop derived {circumflex over (n)} and an {circumflex over (n)} fromsurface proximity could trigger a geometry and mapping update.

Various embodiments are described herein to various apparatuses,systems, and/or methods. Numerous specific details are set forth toprovide a thorough understanding of the overall structure, function,manufacture, and use of the embodiments as described in thespecification and illustrated in the accompanying drawings. It will beunderstood by those skilled in the art, however, that the embodimentsmay be practiced without such specific details. In other instances,well-known operations, components, and elements have not been describedin detail so as not to obscure the embodiments described in thespecification. Those of ordinary skill in the art will understand thatthe embodiments described and illustrated herein are non-limitingexamples, and thus it can be appreciated that the specific structuraland functional details disclosed herein may be representative and do notnecessarily limit the scope of the embodiments, the scope of which isdefined solely by the appended claims.

Reference throughout the specification to “various embodiments,” “someembodiments,” “one embodiment,” or “an embodiment”, or the like, meansthat a particular feature, structure, or characteristic described inconnection with the embodiment is included in at least one embodiment.Thus, appearances of the phrases “in various embodiments,” “in someembodiments,” “in one embodiment,” or “in an embodiment”, or the like,in places throughout the specification are not necessarily all referringto the same embodiment. Furthermore, the particular features,structures, or characteristics may be combined in any suitable manner inone or more embodiments. Thus, the particular features, structures, orcharacteristics illustrated or described in connection with oneembodiment may be combined, in whole or in part, with the featuresstructures, or characteristics of one or more other embodiments withoutlimitation given that such combination is not illogical ornon-functional.

It will be appreciated that the terms “proximal” and “distal” may beused throughout the specification with reference to a clinicianmanipulating one end of an instrument used to treat a patient. The term“proximal” refers to the portion of the instrument closest to theclinician and the term “distal” refers to the portion located furthestfrom the clinician. It will be further appreciated that for concisenessand clarity, spatial terms such as “vertical,” “horizontal,” “up,” and“down” may be used herein with respect to the illustrated embodiments.However, surgical instruments may be used in many orientations andpositions, and these terms are not intended to be limiting and absolute.

1.-20. (canceled)
 21. A system for analyzing signal quality of aplurality of electrodes in contact with a surface of a heart, the systemcomprising: an electronic control unit configured to: acquireelectrophysiology signals from a plurality of electrodes; select atleast one clique of electrodes from the plurality of electrodes; processthe electrophysiology signals from the at least one clique to derive aplurality of local E field data points associated with the at least oneclique of electrodes; and analyze the E field data points associatedwith the at least one clique of electrodes to determine whether aquality of the electrophysiology signals is affected.
 22. The systemaccording to claim 21, wherein, in analyzing the E field data pointsassociated with the at least one clique of electrodes to determinewhether the quality of the electrophysiology signals is affected, theelectronic control unit is further configured to analyze a morphology ofthe electrophysiology signals or determine a peak-to-peak amplituderatio of E_(w)/E_(span).
 23. The system according to claim 21, wherein,in analyzing the E field data points associated with the at least oneclique of electrodes to determine whether the quality of theelectrophysiology signals is affected, the electronic control unit isfurther configured to determine a cross correlation lag between E_(a)and {dot over (φ)}.
 24. The system according to claim 23, wherein theelectronic control unit is further configured to determine whether thecross correlation lag is less than 5 ms.
 25. The system according toclaim 21, wherein, in analyzing the E field data points associated withthe at least one clique of electrodes to determine whether the qualityof the electrophysiology signals is affected, the electronic controlunit is further configured to determine a conduction velocity of atissue adjacent the at least one clique of electrodes.
 26. The systemaccording to claim 25, wherein the electronic control unit is furtherconfigured to compare the conduction velocity of the tissue to aphysiologically plausible conduction velocity to determine a state ofthe tissue.
 27. The system according to claim 25, wherein the state ofthe tissue comprises healthy tissue.
 28. The system according to claim21, wherein the system further comprises: a model construction systemconfigured to obtain a geometry surface model of a cardiac surface ofthe heart; and wherein the electronic control unit is further configuredto determine whether an error in geometric modeling of the cardiacsurface has affected the quality of the electrophysiology signals. 29.The system according to claim 28, wherein, in analyzing the E field datapoints associated with the at least one clique of electrodes todetermine whether the quality of the electrophysiology signals isaffected, the electronic control unit is further configured to determinea catheter force related surface distension of the cardiac surface. 30.The system according to claim 21, wherein the system is configured todetermine whether an artifact is present affecting the quality of theelectrophysiology signals.
 31. The system according to claim 30, whereinthe artifact comprises a far field artifact.
 32. The system according toclaim 21, wherein determining whether the quality of theelectrophysiology signals is affected comprises comparing an E_(span)value against a threshold.
 33. The system according to claim 21, whereinthe electronic control unit is further configured to: derive at leastone orientation independent signal from the at least one clique ofelectrodes; and output catheter orientation independentelectrophysiologic information to a user or process.
 34. The systemaccording to claim 33, wherein the at least one orientation independentsignal comprises one of an instantaneous conduction velocity vector andan index of an inhomogeneous conduction derived from E_(w) or theeccentricity of E_(t).
 35. The system according to claim 21, wherein thesystem further comprises: a model construction system configured toobtain a geometry surface model of a cardiac surface; and wherein theelectronic control unit is further configured to determine whether anerror in geometric modeling of the cardiac surface has affected thequality of the electrophysiology signals.
 36. The system according toclaim 35, wherein in analyzing the E field data points associated withthe at least one clique of electrodes to determine whether the qualityof the electrophysiology signals is affected comprises detecting acatheter force related surface distension of a cardiac surface.
 37. Thesystem according to claim 21, wherein each of the at least one clique ofelectrodes comprises a unipole clique electrode.
 38. The systemaccording to claim 21, wherein determining whether the quality of theelectrophysiology signals is affected comprises comparing a relativetiming of all unipolar clique electrodes.
 39. The system according toclaim 21, wherein determining whether the quality of theelectrophysiology signals is affected comprises comparing a timing ofE_(n) or E_(a) to that of a surface QRS signal.
 40. A method foranalyzing signal quality of a plurality of electrodes in contact with asurface of a heart, comprising: acquiring electrophysiology signals froma plurality of electrodes; selecting at least one clique of electrodesfrom the plurality of electrodes; processing the electrophysiologysignals from the at least one clique to derive a plurality of local Efield data points associated with the at least one clique of electrodes;and analyzing the E field data points associated with the at least oneclique of electrodes to determine whether an artifact is presentaffecting a quality of the electrophysiology signals.